Aims Aging is the most significant contributor to the increasing prevalence of atrial fibrillation (AF). The gut microbiota dysbiosis is involved in age-related diseases. However, whether the aged-associated dysbiosis contributes to age-related AF is still unknown. Direct demonstration that the aged gut microbiota is sufficient to transmit the enhanced AF susceptibility in a young host via microbiota-intestinal barrier-atria axis has not yet been reported. This study aimed to determine whether gut microbiota dysbiosis affects age-related AF. Methods and Results Herein, by using a fecal microbiota transplantation (FMT) rat model, we demonstrated that the high AF susceptibility of aged rats could be transmitted to a young host. Specially, we found the dramatically increased levels of circulating lipopolysaccharide (LPS) and glucose led to the up-regulated expression of NLR family pyrin domain containing 3 (NLRP3)-inflammasome, promoting the development of AF which depended on the enhanced atrial fibrosis in recipient host. Inhibition of inflammasome by a potent and selective inhibitor of the NLRP3 inflammasome, MCC950, resulted in a lower atrial fibrosis and AF susceptibility. Then we conducted cross-sectional clinical studies to explore the effect of aging on the altering trends with glucose levels and circulating LPS among clinical individuals in two China hospitals. We found that both of serum LPS and glucose levels were progressively increased in elderly patients as compared with those young. Furthermore, the aging phenotype of circulating LPS and glucose levels, intestinal structure and atrial NLRP3-inflammasome of rats were also confirmed in clinical AF patients. Finally, aged rats colonized with youthful microbiota restored intestinal structure and atrial NLRP3-inflammasome activity, which suppressed the development of aged-related AF. Conclusions Collectively, these studies described a novel causal role of aberrant gut microbiota in the pathogenesis of age-related AF, which indicates that the microbiota-intestinal barrier-atrial NLRP3 inflammasome axis may be a rational molecular target for the treatment of aged-related arrhythmia disease. Translational Perspective The current study demonstrates that aged-associated microbiota dysbiosis promotes AF in part through a microbiota–gut–atria axis. Increased AF susceptibility due to enhanced atrial NLRP3-inflammasome activity by LPS and high glucose was found in an aged FMT rat model, and also confirmed within elderly clinical individuals. In a long-term FMT rat study, the AF susceptibility was ameliorated by treatment with youthful microbiota. The present findings can further increase our understanding of aged-related AF and address a promising therapeutic strategy that involves modulation of gut microbiota composition.

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This study was performed to characterize the bone metabolism in ten 6-month-old male Goto-Kakizaki (GK) rats, a spontaneous type 2 diabetic model, with ten age- and sex-matched non-diabetic Wistar rats as controls. The femora and the fifth lumbar vertebrae were analyzed by a dual energy X-ray absorptiometry for bone mineral density. Histomorphometrical analyses were performed on the sections from the tibia embedded in methylmethacrylate. Biomechanical characterizations were made by a three-point bending test and a compressive test on the femur and the fifth vertebral body respectively. Compared to the control rats, the bone mineral density was significantly deceased and the histomorphometrical studies showed significantly decreased trabecular bone volume, trabecular thickness and number, osteoid surface and thickness, mineralizing surface, mineral apposition rate and bone formation rate, and also a significant increase in mineralization lag time in the diabetic rats. Strength in both bones and elastic modulus of vertebral body significantly decreased in the diabetic rats as well. In addition, the serum osteocalcin levels were significantly decreased and the serum tartrate-resistant acid phosphatase activity was significantly increased. In conclusion, the 6-month-old GK diabetic rats developed osteopenia with an increased risk of fracture owing to the decreased bone formation, and might be a useful model for unraveling the effects of diabetes on bones independent of obesity frequently seen in the type 2 diabetic patients.

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Autophagy, a bidirectional degradative process extensively occurring in eukaryotes, has been revealed as a potential therapeutic target for several cardiovascular diseases. However, its role in atrial fibrillation (AF) remains largely unknown. This study aimed to determine the role of autophagy in atrial electrical remodeling under AF condition. Here, we reported that autophagic flux was markedly activated in atria of persistent AF patients and rabbit model of atrial rapid pacing (RAP). We also observed that the key autophagy-related gene7 (ATG7) significantly upregulated in AF patients as well as tachypacing rabbits. Moreover, lentivirus-mediated ATG7 knockdown and overexpression in rabbits were employed to clarify the effects of autophagy on atrial electrophysiology via intracardiac operation and patch-clamp experiments. Lentivirus-mediated ATG7 knockdown or autophagy inhibitor chloroquine (CQ) restored the shortened atrial effective refractory period (AERP) and alleviated the AF vulnerability caused by tachypacing in rabbits. Conversely, ATG7 overexpression significantly promoted the incidence and persistence of AF and decreased L-type calcium channel (Cav1.2 α-subunits), along with abbreviated action potential duration (APD) and diminished L-type calcium current (ICa,L). Furthermore, the co-localization and interaction of Cav1.2 with LC3B-positive autophagosomes enhanced when autophagy was activated in atrial myocytes. Tachypacing-induced autophagic degradation of Cav1.2 required ubiquitin signal through the recruitment of ubiquitin-binding proteins RFP2 and p62, which guided Cav1.2 to autophagosomes. These findings suggest that autophagy induces atrial electrical remodeling via ubiquitin-dependent selective degradation of Cav1.2 and provide a novel and promising strategy for preventing AF development.

Enterovirus 71 (EV71) infection can cause severe disease and lead to death in children. Recurring outbreaks of EV71 have been reported in several countries. Interferons (IFNs) have been used for decades to treat several types of viral infection, but have a limited ability to inhibit EV71 replication. Herein, we intend to investigate the mechanisms by which EV71 inhibits the cellular type I IFN response. In this study, MRC-5 (human embryonic lung fibroblast) or RD (human rhabdomyosarcoma) cells were infected with EV71, and then treated with or without IFN-α2b. Cells were harvested and analyzed by flow cytometry to determine the level of IFNAR1. Cell lysis were prepared to detect the levels of STAT1, STAT2, phosphorylated STAT1, phosphorylated STAT2, IFNAR1, JAK1, and TYK2 by Western blotting. The phosphorylation of STAT1 and STAT2 induced by IFN were inhibited without significant downregulation of IFNAR1 in EV71-infected cells. The EV71-induced suppression of STAT1 and STAT2 phosphorylation was not rescued by the protein tyrosine phosphatases inhibitor, and was independent of suppressor of cytokine signaling protein 1/3 levels. The phosphorylation of JAK1 and TYK2 were inhibited accompanied by EV71-induced downregulation of JAK1, which occurred at a post-transcriptional level and was proteasome independent. JAK1 expression did not decrease, and IFN-α-stimulated STAT1 and STAT2 phosphorylation were not blocked in HEK293T cells overexpressing the EV71 viral protein 2A or 3C. This study demonstrates that EV71 inhibits the cellular type I IFN antiviral pathway by downregulating JAK1, while the expression of IFNAR1 does not significantly alter in EV71-infected cells. Additionally, the EV71 viral proteins 2A and 3C do not act as antagonists of cellular type I IFN signaling.

Background Traditional diagnosis methods for lymph node metastases are labor-intensive and time-consuming. As a result, diagnostic systems based on deep learning (DL) algorithms have become a hot topic. However, current research lacks testing with sufficient data to verify performance. The aim of this study was to develop and test a deep learning system capable of identifying lymph node metastases. Methods 921 whole-slide images of lymph nodes were divided into two cohorts: training and testing. For lymph node quantification, we combined Faster RCNN and DeepLab as a cascade DL algorithm to detect regions of interest. For metastatic cancer identification, we fused Xception and DenseNet-121 models and extracted features. Prospective testing to verify the performance of the diagnostic system was performed using 327 unlabeled images. We further validated the proposed system using Positive Predictive Value (PPV) and Negative Predictive Value (NPV) criteria. ResultsWe developed a DL-based system capable of automated quantification and identification of metastatic lymph nodes. The accuracy of lymph node quantification was shown to be 97.13%. The PPV of the combined Xception and DenseNet-121 model was 93.53%, and the NPV was 97.99%. Our experimental results show that the differentiation level of metastatic cancer affects the recognition performance. Conclusions The diagnostic system we established reached a high level of efficiency and accuracy of lymph node diagnosis. This system could potentially be implemented into clinical workflow to assist pathologists in making a preliminary screening for lymph node metastases in gastric cancer patients.

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